Creating 3D Cerebral Cortex Stereoscopic Anatomic Model for Virtual Learning

<b>Objective:</b> To explore the preoperative whole perforator evaluation and intraoperative eccentric design of anterolateral thigh flap (ALTF) based on superficial fascial perforators by modified computed tomography angiography (CTA), and the clinical effects were observed. <b>Methods:</b> A prospective observational study was adopted. Twelve patients with oral and maxillofacial tumors and 10 patients with open injury of the upper limb with large soft tissue defects were hospitalized in the Department of Hand & Microsurgery and Department of Oral & Maxillofacial Surgery of Affiliated Hospital of Binzhou Medical University from January 2021 to July 2022, with 12 males and 10 females, aged from 33 to 75 years, an average age of 56.6 years. The wounds of the patients with oral and maxillofacial tumors were reconstructed by ALTF after the extensive tumor resection and radical cervical lymph node dissection in the same stage; the wounds of the patients with skin and soft tissue defect on the upper limb were covered by ALTF in stage Ⅱ after debridement in stage Ⅰ. After debridement, the area of wound was 3.5 cm×3.5 cm-25.0 cm×10.0 cm and the area of the required flap area was 4.0 cm×4.0 cm-23.0 cm×13.0 cm. Modified CTA scan was performed on the donor site of ALTF before the operation, with the parameters of modified CTA being set to mainly reduce the tube voltage and tube current, and increase the contrast dose and the dual phase scan. The acquired image data were sent to GE AW 4.7 workstation and adopted the volume reconstruction function for visual reconstruction and evaluation of the whole perforator. The information of perforator and source artery was marked on the body surface before operation according to the above evaluation. During the operation, an eccentric flap centered on the visible superficial fascia whole perforator was designed and cut according to the desired flap area and shape. The donor sites of the flap were repaired by direct sutures or full-thickness skin grafts. The total radiation dose was compared between the modified CTA scan and the traditional CTA scan. The distribution of outlet point of perforator of double thighs, the length and direction of superficial fascia perforators based modified CTA were recorded. The type, number, and origin of the target perforator, distribution of of outlet point of perforator, and the diameter, course, and branch of the source artery observed before the operation were compared with those observed during the operation. The healing of donor site wound and the survival of flaps in recipient site were observed after operation. The texture and appearance of flap, oral and upper limb functions, and the functions of femoral donor sites were followed up. <b>Results:</b> The total radiation dose of modified CTA scan was lower than that of the traditional CTA scan. A total of 48 perforators of double thighs were observed, among which, 31 (64.6%) perforators went outward and downward, 9 (18.8%) perforators went inward and downward, 6 (12.5%) perforators went outward and upward, and 2 (4.2%) perforators went inward and upward, and the average length of superficial fascia perforators was 19.94 mm. The preoperative observed type, number, and source of the perforator, the distribution of the outlet point of the perforator, diameter, course, and branches of the source artery were basically consistent with the intraoperative exploration. The types of 15 septocutaneous (including musculoseptocutaneous) perforators and 10 musculocutaneous perforators observed before the operation was consistent with intraoperative exploration. The distance between the mark of the surface perforator point and the actual exit point of the perforator during operation was (0.38±0.11) mm. All flaps survived without vascular crisis. The donor site wounds of 5 cases of skin grafting and 17 cases of direct suturing wounds healed well. The postoperative follow-up was 2 months to 1 year, with an average of 8.2 months, the flaps were soft and slightly bloated; the function of diet and mouth closing was accessible in patients with oral and maxillofacial tumors, the speech function was mildly impaired in patients with tongue cancer, but they could complete basic oral communication; the wrist and elbow joints and forearm rotation function were not significantly limited in patients with upper limb soft tissue injuries; there was no obvious tightness in the donor sites, and the function of the hip and knee joints was not limited. <b>Conclusions:</b> The whole perforator and even the subcutaneous perforator of the donor site of ALTF can be evaluated by modified CTA, and the flap can be used in oral or maxillofacial reconstruction and repair of skin and soft tissue defects of upper limbs to achieve good results. By clarifying the type, number, and source of the perforator, the distribution of the outlet point of the perforator, diameter, course, and branches of the source artery before the operation, the eccentric design of the ALTF based on the superficial fascia perforator was realized. This study has strong guiding value.

Introduction: Guidelines for ascending thoracic aortic aneurysm (ATAA) repair use ATAA diameter, with repair recommended at ≥5.5cm, but ATAA biomechanics may better predict acute type A dissection (ATAD) risk. However, little is known regarding changes in wall stresses among clinically followed patients with &lt;5.5cm ATAA over time. This information is important for patient risk stratification. Hypothesis: We hypothesized that peak ATAA wall stresses would change over time in a patient-specific fashion alongside diameter. Methods: 31 nonsurgical ATAA patients (&lt;5.5cm and growth &lt;0.5cm/year) with computed tomography angiography (CTA) scans taken 3 to 5 years apart were identified. Images were used to construct patient specific three-dimensional ATAA models. Peak diastolic circumferential stresses were determined along the ascending aorta (AA), sinotubular junction (STJ), and aortic sinuses using finite element analysis. Diameters at both time points were measured from CTA scans by a single radiologist blinded to stress results. Stress and diameter distributions were compared using paired t-tests. Results: In the overall population, ATAA diameter increased over time (4.39±0.4 cm vs. 4.43±0.4 cm, p=0.02), while diastolic circumferential stresses along the aorta did not significantly change. However, we found two distinct patient groups: one where wall stresses increased and one where stresses decreased over time. Separate analysis of these groups showed significant changes in circumferential stress in all three aortic regions (488 ± 120 vs. 340 ± 63 kPa for the sinuses, 472 ± 127 vs 345 ± 76 kPa for the STJ and 337 ± 54 vs 277 ± 28 kPa for AA, p&lt;0.001), and significant increase in diameter in the group with increasing stresses (p=0.02). Conclusions: In this nonsurgical group, there is no statically significant change of peak ATAA wall stresses at diastole over 3-5 years. The patients with increased stress were found to be associated with increases in diameter during the corresponding time period. More patient specific data is required to investigate the interaction between wall biomechanics and aortic remodeling. Our results lay the foundation for developing patient-specific ATAD risk predictors for ATAD using patient-specific wall stress changes.

PurposeTo explore the feasibility of transcatheter aortic valve implantation (TAVI) planning computed tomography (CT) on single‐source 8‐cm detector scanners with proper dose control by using two deep‐learning reconstruction algorithms.MethodsReduced‐dose TAVI planning CT was simulated by replacing routine aortic CT angiography (CTA) with a reduced‐dose aortic CTA and a reduced‐dose coronary CTA (Group A, n = 82), while keeping the total dose unchanged. Each of the two CTA scans was processed with a different deep‐learning reconstruction algorithm. Routine‐dose coronary CTA (Group B, n = 86) and routine‐dose aortic CTA (Group C, n = 77) with hybrid iterative reconstruction were used as reference for evaluating the acceptability for surgical planning (A vs. B for aortic valve; A vs. C for access route) and for comparing both the diagnostic and objective image quality (A vs. B for coronary arteries; A vs. C for aortoiliac arteries).ResultsThe mean effective dose in Group A was 8.22 ± 0.83 mSv, representing a 57% reduction of the routine‐dose TAVI planning CT, that is, a routine‐dose coronary CTA plus a routine‐dose aortic CTA on the same scanner model. With respect to B and C, images in A were scored higher for evaluating the aortic valve (p = 0.045) and the access route (p = 0.014) and for diagnosing the thoracic aorta and iliac segments (p < 0.050), while the diagnostic confidence were comparable on the coronary arteries (p > 0.050), abdominal aorta (p = 0.276), and femoral segment (p = 0.816). The image noise in A was found to be 21%–55% lower, leading to a significant increase in contrast‐to‐noise ratio (CNR) by 63%–114% (p < 0.050).ConclusionReduced‐dose TAVI planning CT is feasible on 8‐cm detector scanners by using deep‐learning reconstruction algorithms, showing promise of implementing the examination in imaging settings that are more commonly accessible.

Development of three-dimensional cardiac models from computed tomography angiography

Microcephaly-associated mutations disrupt microtubule-dependent WDR62 translocation from the Golgi complex to the mitotic spindle poles, impair mitotic progression, and alter neurogenic trajectories in patient induced Pluripotent Stem Cell-derived 2D and 3D models of human neurodevelopment.

Application and significance of precise computed tomography angiography (CTA) scanning technology in the assessment of lower extremity arterial diseases.

Background/Objectives: The possibilities of endovascular and minimally invasive treatment of visceral and renal artery aneurysms require precise procedure planning. Accurate visualization of vascular pathologies is crucial in this regard. Expanding diagnostic imaging with real 3D models is one of these methods. The objective of our study was to evaluate the utility of 3D printing and virtual 3D models in visualizing visceral and renal artery aneurysms. Methods: A group of 30 patients with true aneurysms of the visceral and renal arteries was selected based on computed tomography angiography (CTA). Aneurysm morphology, diameters, arterial diameters, and anatomical vessel variants were analyzed. Imaging data were processed and 3D-printed using Fused Filament Fabrication (FFF) technology. The resulting 3D models were measured, and dimensional deviations were compared to radiological images. Results: The cohort included 51 aneurysms across arteries supplying abdominal organs, with splenic artery aneurysms (49%) and renal artery aneurysms (25.5%) predominating. Half of the patient group had multiple aneurysms, and 36.7% exhibited anatomical arterial variants. Forty-three 3D models of visceral and renal artery aneurysms were generated, accurately depicting isolated vascular pathologies and the course of visceral arteries in regions of interest. Measurement analysis confirmed that the 3D-printed models showed a mean dimensional deviation of 0.24 mm compared to radiological images. Conclusions: 3D-printed and virtual models enhance the analysis of vascular pathologies, significantly improving the assessment of pathological changes and visualization of anatomical details, especially in hilar aneurysms and aneurysm branches.

Kidney structures segmentation is a crucial yet challenging task in the computer-aided diagnosis of surgery-based renal cancer. Although numerous deep learning models have achieved remarkable success in many medical image segmentation tasks, accurate segmentation of kidney structures on computed tomography angiography (CTA) images remains challenging, due to the variable sizes of kidney tumors and the ambiguous boundaries between kidney structures and their surroundings. In this paper, we propose a boundary-aware network (BA-Net) to segment kidneys, kidney tumors, arteries, and veins on CTA scans. This model contains a shared encoder, a boundary decoder, and a segmentation decoder. The multi-scale deep supervision strategy is adopted on both decoders, which can alleviate the issues caused by variable tumor sizes. The boundary probability maps produced by the boundary decoder at each scale are used as attention to enhance the segmentation feature maps. We evaluated the BA-Net on the Kidney PArsing (KiPA) Challenge dataset and achieved an average Dice score of 89.65 $$\%$$ for kidney structures segmentation on CTA scans using 4-fold cross-validation. The results demonstrate the effectiveness of the BA-Net. Code and pre-trained models are available at https://github.com/ShishuaiHu/BA-Net .

Objective: To explore the establishment and application of three-dimensional model of deep inferior epigastric artery perforator flap based on computed tomography angiography (CTA). Methods: Six patients with breast absence after modified radical mastectomy because of breast cancer, 5 patients with congenital absence of vagina, and 6 patients with Paget's disease of penis and scrotum were hospitalized in our unit from January 2012 to April 2017. The size of wounds after excision of the lesion or that of flaps needed for reconstruction ranged from 17 cm×5 cm to 25 cm×9 cm. Abdominal CTA was performed before the surgery, and data of CTA were sent to CT workstation to make three-dimensional model of deep inferior epigastric artery perforator flap according to shape and size of wound. The number, course, and location of deep inferior epigastric artery, vein, and their perforators, and the superficial inferior epigastric vein were observed in the above-mentioned three-dimensional model. The rectangular plane coordinate system with the umbilicus as the origin was established to locate and observe course and type of the largest deep inferior epigastric artery perforator in left and right side. Deep inferior epigastric artery perforator flaps were designed and deep inferior epigastric artery perforators etc. were marked according to three-dimensional models of the flaps before the surgery. The condition observed in three-dimensional model of the flap was compared with the clinical condition in the surgery of free transverse bilateral deep inferior epigastric artery perforator flap transplantation for breast reconstruction and longitudinal pedicled thinned unilateral deep inferior epigastric artery perforator flap transplantation for vagina reconstruction and wound repair of Paget's disease of penis or scrotum. The size of flap ranged from 17 cm×6 cm to 25 cm×10 cm. Results: Seventeen three-dimensional models of deep inferior epigastric artery perforator flaps were established, including 6 bilateral models and 11 unilateral models. Seventy-two reliable deep inferior epigastric artery perforators were observed in the three-dimensional model with 3.2±0.7 in the right and 3.1±0.8 in the left. The locations of the largest deep inferior epigastric artery perforators in the right and left were [(-3.2±1.4) cm, (-1.0±0.7) cm] and [(4.0±1.2) cm, (-1.2±1.1) cm] respectively. Fourteen largest deep inferior epigastric artery perforators coursed directly and nine coursed tortuously in the rectus muscle. Twenty-three superficial inferior epigastric veins were detected in the three-dimensional models of the flaps. The number, location, and course of deep inferior epigastric artery and vein and superficial inferior epigastric vein observed in the three-dimensional model of deep inferior epigastric artery perforator flap were in accordance with the condition observed in the surgery. Seventy reliable deep inferior epigastric artery perforators were detected in the surgery, and the other 2 perforators were unclear due to bleeding. Course of these perforators were in accordance with the condition observed in the three-dimensional model. Deep inferior epigastric artery perforator flaps of all patients survived well with no complication except that 1 patient suffered from delayed healing of wound in perineum. During follow-up of 1 to 12 months, all flaps survived with good shape and texture. Conclusions: The three-dimensional model of deep inferior epigastric artery perforator flap based on CTA can be established easily and can provide information of number, location, and course of deep inferior epigastric artery, vein, and their perforators, and superficial inferior epigastric vein to guide preoperative design and intraoperative dissection of the flap effectively.

Fenestrated endovascular aortic aneurysm repair (FEVAR) is used in pararenal abdominal aortic aneurysms to achieve a durable proximal seal. This study investigated the mid-term course of the proximal fenestrated stent graft (FSG) sealing zone on the first and latest available post-FEVAR computed tomographic angiography (CTA) scan in a single-center series. In 61 elective FEVAR patients, the shortest length of circumferential apposition between the FSG and the aortic wall (shortest apposition length [SAL]) was retrospectively assessed on the first and last available postoperative CTA scans. Patient records were reviewed for FEVAR-related procedural details, complications, and reinterventions. The median (interquartile range) time between the FEVAR procedure and the first and last CTA scan was 35 (30-48) days and 2.6 (1.2-4.3) years, respectively. The median (interquartile range) SAL was 38 (29-48) mm, and 44 (34-59) mm on the first and last CTA scans, respectively. During follow-up, the SAL increased >5 mm in 32 patients (52%), and decreased >5 mm in six patients (10%). Reintervention was performed for a type 1a endoleak in one patient. Twelve other patients needed 17 reinterventions for other FEVAR-related complications. Good mid-term apposition of the FSG in the pararenal aorta was achieved post-FEVAR, and the occurrence of type 1a endoleaks was low. The number of reinterventions was substantial, however, but for reasons other than loss of proximal seal.

Abdominal Aortic Aneurysm (AAA) is still a socially relevant public health challenge, evidenced by an 82.1% increase in associated fatalities from 1990 to 2019 (with 172,427 deaths in 2019 alone). In a clinical setting, computed tomography angiography (CTA) is the imaging modality of choice for monitoring and/or presurgical planning of AAA patients. However, manual segmentation of CTA images is labor intensive and time consuming. Hence, there is a growing need for automated segmentation algorithms, particularly when these influence treatment planning. The deep-learning pipeline proposed in this work is designed to automatically segment AAA CTA images. The framework adapted a fully developed patch-based dilated modified U-Net model, which shows remarkable efficiency in accurately delineating AAA regions within the CTA scans. During the prediction phase, the deep learning architecture demonstrates exceptional speed, requiring 17 ± 0.02 milliseconds per frame to generate the final segmented output. Building upon this work, we included the application of Non-Uniform Rational B-Splines (NURBS) to enhance the segmentation process. This advancement is essential in addressing the critical need for clinical accuracy in medical image segmentation. NURBS enables the creation of continuous curves that seamlessly conform to the intricate contours of anatomical structures, offering a significant improvement in segmentation accuracy. Through the integration of advanced deep learning architectures and the precision of NURBS for segmentation refinement, coupled with the fast processing time and accurate segmentation, the the proposed model represents a promising clinical tool that can be used in the clinical management of AAAs.

Just as the increasing awareness level of the stereoscopic cinema, so the perception of limitations while watching movies with 3D glasses has been emerged as well. It is not only that the additional glasses are uncomfortable and annoying; there are some tangible arguments for avoiding 3D glasses. These “stereoscopic deficits” are caused by the 3D glasses itself. In contrast to natural viewing with naked eyes, the artificial 3D viewing with 3D glasses introduces specific “unnatural” side effects. The most of the moviegoers has experienced unspecific discomfort in 3D cinema, which they may have associated with insufficient image quality. Obviously, quality problems with 3D glasses can be solved by technical improvement. But this simple answer can -and already has- mislead some decision makers to relax on the existing 3D glasses solution. It needs to be underlined, that there are inherent difficulties with the glasses, which can never be solved with modest advancement; as the 3D glasses initiate them. To overcome the limitations of stereoscopy in display applications, several technologies has been proposed to create a 3D impression without the need of 3D glasses, known as autostereoscopy. But even todays autostereoscopic displays cannot solve all viewing problems and still show limitations. A hyperview display could be a suitable candidate, if it would be possible to create an affordable device and generate the necessary content in an acceptable time frame. All autostereoscopic displays, based on the idea of lightfield, integral photography or super-multiview could be unified within the concept of hyperview. It is essential for functionality that every of these display technologies uses numerous of different perspective images to create the 3D impression. Such a calculation of a very high number of views will require much more computing time as for the formation of a simple stereoscopic image pair. The hyperview concept allows to describe the screen image of any 3D technology just with a simple equation. This formula can be utilized to create a specific hyperview matrix for a certain 3D display – independent of the technology used. A hyperview matrix may contain the references to loads of images and act as an instruction for a subsequent rendering process of particular pixels. Naturally, a single pixel will deliver an image with no resolution and does not provide any idea of the rendered scene. However, by implementing the method of pixel recycling, a 3D image can be perceived, even if all source images are different. It will be proven that several millions of perspectives can be rendered with the support of GPU rendering and benefit from the hyperview matrix. In result, a conventional autostereoscopic display, which is designed to represent only a few perspectives can be used to show a hyperview image by using a suitable hyperview matrix. It will be shown that a millions-of-views-hyperview-image can be presented on a conventional autostereoscopic display. For such an hyperview image it is required that all pixels of the displays are allocated by different source images. Controlled by the hyperview matrix, an adapted renderer can render a full hyperview image in real-time.

Application value of iterative reconstruction with computed tomographic angiography (CTA) in the patients with intractable headache was investigated. One hundred and eighty patients with headache, who were admitted and treated in Cangzhou Central Hospital, were selected to undergo CTA scan. The patients were divided into group A, B and C according to different scanning conditions and data reconstruction techniques. In group A, the scanning parameters were 120 kV and 300 mA, and filtered back projection (FBP) algorithm was used for data reconstruction. In group B, the scan parameters were 100 kV and automatic milliamperes. Further, adaptive iterative dose reduction via three-dimensional processing (AIDR-3D) was used for data reconstruction. In group C, the scan parameters were 80 kV with automatic milliamperes, and AIDR-3D technique was utilized for data reconstruction. The CT value, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective assessment score of image quality and radiation dose of the three groups of images were compared. There were significant differences in CT values, standard deviation (SD) values, SNRs and CNRs of different vessel segments and muscles among the three groups (P<0.05). The image assessment scores at the levels of the atlas and C7 vertebra as well as those of the brain parenchyma in the three groups had notable differences (P<0.05). However, they showed no differences at the level of the C4 vertebra (P>0.05). Further, significant differences were observed in volume computed tomography dose index (CTDIvol), dose-length product (DLP) and effective dose (ED) (P<0.05). In conclusion, for patients with intractable headache, the image quality of the CTA scan using AIDR-3D reconstruction method showed better results over FBP reconstruction method. Further, best results were observed when the scan parameters were 100 kV, automatic milliamperes and the data reconstruction was performed by AIDR-3D.

The aorta is the largest vessel of the human body and its pathological degenerations, such as dissections and aneurysms, can be life threatening. An automatic and fast segmentation of the aorta can therefore be a helpful tool to quickly identify an abnormal anatomy. The segmentation of the aortic vessel tree (AVT) typically requires extensive manual labor, but, in recent years, progress in deep learning techniques made the automation of this process viable. For this purpose, we tested different deep learning networks to segment the aortic vessel tree from computed tomography angiography (CTA) scans with a deep neural network consisting of an encoder-decoder architecture with skip connections and an optional self-attention block. The networks were trained on a dataset of 56 CTA scans from three different sources and resulted in Dice score similarities between 0.043−0.897. Generally, the classical U-Nets performed better than the ones containing a self-attention block, indicating that they might diminish performance for AVT segmentation. The quality of the resulting segmentations was highly dependent on the CTA image quality, especially on the contrast between the aorta and the surrounding tissues. However, the trained deep neural network can segment CTA scans well with limited computational resources and training data.

Image-based 3D shape reconstruction is essential for 3D modeling in recognition, virtual reality, generation of video games, 3D animation, and in the creation of 3D virtual fitting rooms - the sought-after application in this dissertation. In this work, we propose a novel reconstruction method that uses a generic 3D model that roughly controls the overall reconstruction shape which in turn, reduces the number of 2D images needed to just two (frontal and profile) for obtaining a 3D point model. The generic model consists of a massive set of 3D points that lack saliency, topological meaning, and relational interconnections. This is also true about points in the two canonical images. In this work, we propose finding a small set of interconnected ordered intrinsic salient points (control points) residing on the silhouette of the projections of the generic model onto the two image spaces, as well as finding those for the canonical images. Points on the generic model and the images are automatically given saliency with order and interconnections through loop-subdivision operating on those control points and their equivalent points on the canonical images. The transformation of the generic model into the specific object is done through morphing the points on the generic model to follow and be consistent with their equivalent points on the canonical images. The control points on the canonical images are automatically obtained using an active shape model (ASM) that modifies an average trained control point set attained using an offline training, to account for class shape variability and boundary regularization guaranteeing the control points to reside on the silhouette (boundary) of the individual. The reconstructed 3D model is furtherly refined through smoothing the reconstructed surface, while fixing local holes using a principle component analysis (PCA) decomposition. This reconstruction method is convenient, simple, efficient, and results in an average geometric error of less than 0.5% over 700 diverse body models from the CAESAR dataset. We then implement the contour-based articulated model to the personalized 3D model for pose recovery. The evolution of the model through the articulation process is captured in a video clip. 3D transformations are found and applied to the 3D model on its parts so that the projections of the 3D model 'match' those observed in the video sequence at corresponding frames. This is done by minimizing the error between the frontal projection body region points and the target points from the image for each independent moving part, with sub-resolution recovery errors. Once the personalized 3D model is obtained and the articulated model is implemented, the algorithm simulates how garments virtually appear on the reconstructed person under different poses. Different types of clothes are classified as tight or loose, where for the first type of garments, the garment is mapped onto the person's body, whereas for the second type, the mapping adjusts to accommodate the loose nature of the garment, and its fitting on the body of the reconstructed person model. This creates a virtual in-home fitting room for garment fitting, which is timely and is a needed application that would go hand in hand with online clothes shopping, allowing the trying of garments at home with changing poses before ordering them, and can be updated as often as necessary to accommodate changes in physique, weight, aging, etc. This is also done with minimum requirements from the user aside from taking two images and a video of pose articulations using their cam or smart phone, and stands as a useful, needed, and attractive App.